Features
From WandoraWiki
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This page summarizes perhaps the most fundamental features of Wandora application. | This page summarizes perhaps the most fundamental features of Wandora application. | ||
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* Fast and reliable | * Fast and reliable | ||
* Requires Java 1.6 | * Requires Java 1.6 | ||
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== Graphical user interface == | == Graphical user interface == | ||
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* Topic map browser | * Topic map browser | ||
* Graph visualization of a topic map | * Graph visualization of a topic map | ||
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== [[Introduction to Layered Topic Maps|Layered representation of knowledge]] == | == [[Introduction to Layered Topic Maps|Layered representation of knowledge]] == | ||
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* Protect some parts of topic map by allowing only read access | * Protect some parts of topic map by allowing only read access | ||
* Use nested layer stacks to create tree like layer structures | * Use nested layer stacks to create tree like layer structures | ||
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== Several data storage options == | == Several data storage options == | ||
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* [[Memory topic map|Memory based topic map]] for very fast processing of relatively small topic maps | * [[Memory topic map|Memory based topic map]] for very fast processing of relatively small topic maps | ||
* [[Database topic map|Relational database storage]] makes it possible to use topic maps of virtually unlimited size | * [[Database topic map|Relational database storage]] makes it possible to use topic maps of virtually unlimited size | ||
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== Import data in several formats == | == Import data in several formats == | ||
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* [[Importing XML with XSL|Imports any valid XML document with proper XSL converting the XML to XTM]] | * [[Importing XML with XSL|Imports any valid XML document with proper XSL converting the XML to XTM]] | ||
* [[Transferring data with clipboard|Clipboard import and export of topics and associations]] | * [[Transferring data with clipboard|Clipboard import and export of topics and associations]] | ||
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== Extract topic maps from various sources == | == Extract topic maps from various sources == | ||
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And many more... | And many more... | ||
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== Search and analyze topic maps == | == Search and analyze topic maps == | ||
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* [[Topic map connection statistics|Topic map connection count and distribution]] (Topic map degree distribution). | * [[Topic map connection statistics|Topic map connection count and distribution]] (Topic map degree distribution). | ||
* [[SOM classifier]] to analyze topics with associations. | * [[SOM classifier]] to analyze topics with associations. | ||
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== Publish knowledge == | == Publish knowledge == | ||
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* [[Lucene search index export|Create and export Lucene search index from any topic map]]. | * [[Lucene search index export|Create and export Lucene search index from any topic map]]. | ||
* Download subject locator URLs and occurrence URLs. | * Download subject locator URLs and occurrence URLs. | ||
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== Generate simple topic map graphs == | == Generate simple topic map graphs == | ||
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* [[Edge generator]] | * [[Edge generator]] | ||
* [[L-system generator|Generate topic maps with L-systems]]. | * [[L-system generator|Generate topic maps with L-systems]]. | ||
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== [[Tool manager|Plugin architecture makes it easy to add custom functionality]] == | == [[Tool manager|Plugin architecture makes it easy to add custom functionality]] == | ||
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* Customized ways to represent the data in the topic map | * Customized ways to represent the data in the topic map | ||
* Custom publishing methods | * Custom publishing methods | ||
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== Upcoming features == | == Upcoming features == | ||
Revision as of 10:06, 15 June 2011
This page summarizes perhaps the most fundamental features of Wandora application.
Desktop Application
- Fast and reliable
- Requires Java 1.6
Graphical user interface
- Topic map browser
- Graph visualization of a topic map
Layered representation of knowledge
- Construct the knowledge using several different layers, each containing only part of the knowledge
- You can view only parts of data and hide parts that don't interest you
- Automatic merging of different and even distributed data sources
- Protect some parts of topic map by allowing only read access
- Use nested layer stacks to create tree like layer structures
Several data storage options
- Memory based topic map for very fast processing of relatively small topic maps
- Relational database storage makes it possible to use topic maps of virtually unlimited size
Import data in several formats
- Imports topic maps in XTM, LTM, and JTM formats
- Imports RDF data in RDF, N3 and Turtle formats
- Imports OBO flat file format ontologies such as The Gene Ontology
- Imports any valid XML document with proper XSL converting the XML to XTM
- Clipboard import and export of topics and associations
Extract topic maps from various sources
Over 50 different data format and web service extractors. Including
- MP3 ID3v1 and ID3v2 extractor
- JPG binary metadata extractor
- PDF extractor
- Email extractor
- File system extractor
- HTML link extractor
- IMDB extractor
- FreeDB extractor
- Wikipedia extractor and more general MediaWiki extractor
- Last.fm extractors
- Bibtex extractor
- RIS extractor
- Convert simple HTML tables to topic map associations
- Convert simple HTML lists to topic maps
- Simple Text Document Extractor
- RSS 2.0 Extractor
- Atom extractor
- Microformat extractors
- Flickr extractors
- YouTube extractor
- OpenCalais classifier
- OpenCyc extractor
- Geonames extractors
- SKOS RDF extractor
- Dublin Core RDF extractor
- FOAF RDF extractor
- Gellish ontology extractor
- Subj3ct record extractor
- DBpedia extractor
- SPARQL extractor
And many more...
Search and analyze topic maps
- Search topics with regular expressions, find similar topics, and use Wandora's query language to perform more complex searches.
- Compare topic maps.
- Clustering coefficient for any topic set including average clustering coefficient of a topic map.
- Topic map diameter and average path length.
- Topic map connection count and distribution (Topic map degree distribution).
- SOM classifier to analyze topics with associations.
Publish knowledge
- Embedded HTTP server allows you to publish topic maps as a dynamic HTML site, RSS feed or pretty much anything if you just write suitable templates for your output.
- Included outputs: HTML, RSS instance feed, ATOM topic, Wandora Web Service.
- We have created several Wandora Drupal extras to show you examples how Wandora can be used together with Drupal content management system.
- We have also created an extra for Joomla content management system to demonstrate how to publish Wandora content in Joomla sites.
- Build your own topic map application using Wandora's Web Service.
- You can also create new output modules to Wandora easily. See chapter Setting up new services at Embedded HTTP server.
- Export the topic map as a collection of static HTML pages.
- Export topic maps as Graph Modeling Language, GraphML, and GraphXML graphs.
- Wandora Piccolo combination allows you to set up a large scale dynamic WWW site based on the topic maps.
- Create and export Lucene search index from any topic map.
- Download subject locator URLs and occurrence URLs.
Generate simple topic map graphs
- Random graph generator
- Fully connected graph generator
- Tree graph generator
- Linear list graph generator
- Finite group graph generator
- Platonic solid graph generator
- Hypercube graph generator
- Tiling graph generator
- Edge generator
- Generate topic maps with L-systems.
Plugin architecture makes it easy to add custom functionality
- Tools that process topic map, for example cleaning or reconstructing data
- Importing data in different formats, for example from existing relational database
- Exporting data in different formats
- Reading and automatic processing of metadata from a collection of files
- Customized ways to represent the data in the topic map
- Custom publishing methods
Upcoming features
Wandora Team releases new features frequently. Features under development have been reviewed in wiki page Upcoming features.
Now you might want to continue to
- Wandora Download
- View Wandora Screenshots
- Browse Wandora's Documentation
